The multivariate index allows the selection of white-grain maize hybrids in contrasting environments
DOI:
https://doi.org/10.26848/rbgf.v18.3.p1886-1901Keywords:
adaptability, Lins Bins, Zea mays L., agronomic, physiologicalAbstract
Maize is a crop of great economic, social and cultural importance in many countries worldwide, especially in Mexico. The objective of this work was to use a multivariate index to select white grain maize hybrids through agronomic and physiological traits obtained in two environments. A factorial design (2 × 15) was used: two environments (E1 and E2) and 15 hybrids, with four replications. The analysis of variance showed highly significant differences for all nine agronomic and eight physiological variables evaluated when considering the effect of environment and hybrids. The number of rows per ear and root water potential, did not show interactions between factors. The heritabilities of the agronomic and physiological characteristics ranged from 5.85 to 75.88 and from 42.41 to 99.82%, respectively. High variability was found among hybrids in the two environments for the two sets of traits evaluated. The determination of a multivariate index from the index proposed by Lins Bins (Pi) allowed us to obtain three multivariate indices associated with agronomic (Pim-agro), physiological (Pim-physiol) and their combination (PimAgro+Phisiol) characteristics. The selection through these indices showed that it is possible to identify hybrids with high stability and general adaptability with favorable characteristics in white maize for the evaluated environments and showed the possibility of improving the selection criteria by using of the proposed multivariate index.
Downloads
References
Aguilera, J.G., Minozzo, J.A.D., Barichello, D., Fogaça, C.M., da Silva, J.P. Jr, Consoli, L., Pereira, J.F., 2016. Alleles of organic acid transporter genes are highly correlated with wheat resistance to acidic soil in field conditions. Theor Appl Genet. 129(7), 1317-1331. https://doi.org/10.1007/s00122-016-2705-3.
Aguilera, J.G., Teodoro, P.E., da Silva, J.P., Pereira, J.F., Zuffo, A.M., Consoli, L., 2019. Selection of Aluminum‐Resistant Wheat Genotypes Using Multienvironment and Multivariate Indices. Agronomy Journal, 111(6), 2804-2810. https://doi.org/10.2134/agronj2019.06.0470
Alam, M.A., Rahman, M., Ahmed, S., Jahan, N. et al., 2022. Genetic variation and genotype by environment interaction for agronomic traits in maize (Zea mays L.) hybrids. Plants, 11(11), 1522. https://doi.org/10.3390/plants11111522
Almeida, H.C., Soares, A.P.L., Poersch, N.L., Izidorio, T.H., Teodoro, L.P.R., Teodoro, P.E., 2021. Adaptability and stability of soybean cultivars in the region of Chapadões. Revista Ceres, 68:326-332. https://doi.org/10.1590/0034-737X202168040010
Beyene, Y., Semagn, K., Mugo, S., Prasanna, B.M. et al., 2016. Performance and grain yield stability of maize populations developed using marker-assisted recurrent selection and pedigree selection procedures. Euphytica 208, 285-297. https://doi.org/10.1007/s10681-015-1590-1
Bhering, L.L., Cruz, C.D., de Vasconcelos, E.S., Ferreira, A., de Resende, Jr M.F.R., 2008. Alternative methodology for Scott‒Knott test. Crop Breeding and Applied Biotechnology 8(1). https://doi.org/10.12702/1984-7033.v08n01a02
Bhering, L.L., 2017. Rbio: A Tool For Biometric And Statistical Analysis Using The R Platform. Crop Breeding and Applied Biotechnology, 17(2), 187-190. https://doi.org/10.1590/1984-70332017v17n2s29
Buenrostro-Robles, M., Lobato-Ortiz, R., García-Zavala, J.J., Sánchez-Abarca, C., 2017. Rendimiento de líneas de maíz exótico irradiado con rayos gamma y de híbridos de cruza simple. Revista Fitotecnia Mexicana, 40(3):351-358. https://doi.org/10.35196/rfm.2017.3.351-358
Coca, E.H.H., Diaz, A.V.C., Jiménez, J.E., 2019. Heterosis útil y caracteres asociados al rendimiento en híbridos de maíz amarillo duro bajo condiciones de secano en Tarapoto. Análes científicos, 80(1):259-268. http://dx.doi.org/10.21704/ac.v80i1.1393
Djidonou, D., Leskovar, D.I., Joshi, M., et al., 2020. Stability of yield and its components in grafted tomato tested across multiple environments in Texas. Scientific Reports, 10(1), 13535. https://doi.org/10.1038/s41598-020-70548-3
do Couto, D.P., Oliveira, W.B.D.S., de Oliveira, J.S., et al., 2023. Analysis of the Effect of the Interaction of Genotype and Environment on the Yield Stability of Maize Varieties. Genetic Resources for Breeding. Agronomy, 13(8), 1970. https://doi.org/10.3390/agronomy13081970
Donovan, J., Rutsaert, P., Domínguez, C., Peña, M., 2022. Capacities of local maize seed enterprises in Mexico: Implications for seed systems development. Food Security, 14, 509–529. https://doi.org/10.1007/s12571-021-01247-8
Ewu, Y., Messing, J., 2014. Proteome balancing of the maize seed for higher nutritional value. Front. Plant Sci., 5, 240. https://doi.org/10.3389/fpls.2014.00240
Gabriel, A., Faria, M.V., Battistelli, G.M., Rossi, E.S., Da Silva, C.A., De Marck, D.F., Gava, E., 2018. Desempenho agronômico e estabilidade de topcrosses de milho avaliados em Minas Gerais e Paraná. Revista Brasileira de Milho e Sorgo, 17(2), 303-316. https://doi.org/10.18512/1980-6477/rbms.v17n2p303-316
Greveniotis, V., Bouloumpasi, E., Zotis, S., Korkovelos, A., Ipsilandis, C.G., 2021. Estimations on trait stability of maize genotypes. Agriculture, 11(10), 952. https://doi.org/10.3390/agriculture11100952
Jahangirlou, M.R., Akbari, G.A., Alahdadi, I., Soufizadeh, S., Parsons, D., 2020. Grain quality of maize cultivars as a function of planting dates, irrigation and nitrogen stress: a case study from semiarid conditions of Iran. Agriculture 11(1), 11. https://doi.org/10.3390/agriculture11010011
LaFevor, M.C., 2022. Spatial and temporal changes in crop species production diversity in Mexico (1980–2020). Agriculture 12(7), 985. https://doi.org/10.3390/agriculture12070985
Lin, C.S., Binns, M.R., 1988. A method of analyzing cultivar x location x year experiments: a new stability parameter. Theoretical and Applied Genetics, 76, 425-430. https://doi.org/10.1007/BF00265344
Linares-Holguín, O.O., Rocandio-Rodríguez, M., Santacruz-Varela, A., López-Valenzuela, J.Á., Córdova-Téllez, L., Parra-Terraza, S., ... Sánchez-Peña, P., 2019. Caracterización fenotípica y agronómica de maíces (Zea mays ssp. mays L.) nativos de Sinaloa, México. Interciencia, 44(7), 421-428.
Menezes, C.B., Tardin, F.D., Portugal, A.F., Ribeiro, A.D.S., De Carvalho, A.J., De Almeida, F.H.L., ... Dos Santos, C.V., 2015. Adaptabilidade e estabilidade de linhagens de sorgo em ambientes com e sem restrição hídrica. Revista Brasileira de Milho e Sorgo, 14(1), 101-115.
Ocwa, A., Harsanyi, E., Széles, A., Holb, I.J., Szabó, S., Rátonyi, T., Mohammed, S., 2023. A bibliographic review of climate change and fertilization as the main drivers of maize yield: implications for food security. Agriculture Food Security, 12(1), 1-18. https://doi.org/10.1186/s40066-023-00419-3
Partelli, F.L., da Silva, F.A., Covre, A.M., Oliosi, G., Correa, C.C.G., Viana, A.P., 2022. Adaptability and stability of Coffea canephora to dynamic environments using the Bayesian approach. Scientific Reports, 12(1), 11608. https://doi.org/10.1038/s41598-022-15190-x
Peixoto, M.A., Evangelista, J.S.P.C., Coelho, I.F., Carvalho, L.P., Farias, F.J.C., Teodoro, P.E., Bhering, L.L., 2022. Genotype selection based on multiple traits in cotton crops: The application of genotype by yield*trait biplot. Acta Scientiarum. Agronomy, 44, e54136. https://doi.org/10.4025/actasciagron.v44i1.54136
Pierre, J.F., Latournerie-Moreno, L., Garruña-Hernández, R., Jacobsen, K.L., Guevara-Hernández, F., Laboski, C.A., Ruiz-Sánchez, E., 2022. Maize legume intercropping systems in southern Mexico: A review of benefits and challenges. Ciência Rural, 52, e20210409. https://doi.org/10.1590/0103-8478cr20210409
Ponce-Encinas, M.C., López-Morales, F., Chura-Chuquija, J., Hernández-Leal, E., Hernández-Salinas, G., Aragón-García, A., 2022. Interacción genotipo-ambiente del rendimiento en híbridos de maíz amarillo mediante AMMI y SREG. Revista mexicana de ciencias agrícolas, 13(7), 1247-1258. https://doi.org/10.29312/remexca.v13i7.3070
Prakash, L., Prathapasenan, G., 1988. Effect of NaCl salinity and putrescine on shoot growth, tissue ion concentration and yield of rice (Oryza sativa L. var. GR-3). Journal of Agronomy and Crop Science 160(5), 325-34. https://doi.org/10.1111/j.1439-037X.1988.tb00630.x
Rebolloza-Hernández, H., Cervantes-Adame, Y.F., Broa-Rojas, E., Bahena-Delgado, G., Olvera-Velona, A., 2020. Fenotipeo y selección de líneas S1 segregantes de maíz tolerantes a estrés hídrico. Biotecnia, 22(3), 20-28.
Russell, W.A., Hallauer, A.R., 1980. Maize. Hybridization of crop plants, 299-312. https://doi.org/10.2135/1980.hybridizationofcrops.c19
Saavedra Guevara, C., Pérez López, D.D.J., González Huerta, A., Franco Martínez, J., Rubí Arriaga, M., Ramírez Dávila, J.F., 2021. Métodos de Griffing: revisión sobre su importancia y aplicación en fitomejoramiento convencional. Revista mexicana de ciencias agrícolas, 12(7), 1275-1286. https://doi.org/10.29312/remexca.v12i7.3040
Sadok, W., Schoppach, R., 2019. Potential involvement of root auxins in drought tolerance by modulating nocturnal and daytime water use in wheat. Annals of botany, 124(6), 969-978. https://doi.org/10.1093/aob/mcz023
Steiner, F., Zuffo, A.M., Teodoro, P.E., Aguilera, J.G., Teodoro, L.P.R., 2021. Multivariate adaptability and stability of soya bean genotypes for abiotic stresses. Journal of Agronomy and Crop Science, 207(2), 354-361. https://doi.org/10.1111/jac.12446
Teodoro, P.E., Farias, F.J.C., de Carvalho, L.P., Ribeiro, L.P., Nascimento, M., Azevedo, C.F., ... Bhering, L.L., 2019. Adaptability and stability of cotton genotypes regarding fiber yield and quality traits. Crop Science, 59(2), 518-524. https://doi.org/10.2135/cropsci2018.04.0250
Zuffo, A.M., Steiner, F., Aguilera, J.G., et al., 2022. Selected Indices to Identify Water-Stress-Tolerant Tropical Forage Grasses. Plants, 11(18), 2444. https://doi.org/10.3390/plantE11182444
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Lorenzo Pérez-López, Leandris Argentel-Martínez, Ofelda Peñuelas-Rubio Peñuelas-Rubio, Francisco Cervantes-Ortiz, Frank Denis Torres Huaco, Cesar Leobardo Aguirre-Mancilla, Jorge González Aguilera, Paulo Eduardo Teodoro

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Revista Brasileira de Geografia Física agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted to make their work available online before or during the editorial process, on academic social networks, digital repositories, or preprint servers. After publication in Revista Brasileira de Geografia Física, authors are expected to update the preprint or postprint versions on the platforms where they were originally made available, providing a link to the final published version and any other relevant information, with proper recognition of authorship and the initial publication in this journal.
You are free to:
Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
Adapt — remix, transform, and build upon the material for any purpose, even commercially.
The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.